Publications by authors named "Sophyani B Yussif"
Feature extraction plays a critical role in text classification, as it converts textual data into numerical representations suitable for machine learning models. A key challenge lies in effectively capturing both semantic and contextual information from text at various levels of granularity while avoiding overfitting. Prior methods have often demonstrated suboptimal performance, largely due to the limitations of the feature extraction techniques employed.
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- Recent advancements in machine learning, particularly deep learning, help in recognizing and classifying COVID-19 in medical images, but they struggle with feature extraction, which leads to less accurate results.
- This study introduces Dual_Pachi, an innovative framework designed for improved feature extraction from chest X-rays, utilizing a structure that includes converting images into specific color spaces and employing a multi-head self-attention mechanism.
- Testing shows that Dual_Pachi significantly outperforms traditional deep learning methods, achieving high accuracy levels while also providing visual insights into how attention is applied in the classification process.